Automatic Generation of Stair-ascending Gait for Snake Robot Using Genetic Algorithms
| Autor: | Yuan-Lin Liu, 劉遠霖 |
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| Rok vydání: | 2009 |
| Druh dokumentu: | 學位論文 ; thesis |
| Popis: | 97 In the study, we propose a generalized structure for articulated snake robots to move towards the aim position when ascending the stairs. In addition, we exploit Genetic Algorithms to automatically generate stair-ascending gaits for snake robots. Since there is no systematic approach for planning stair-ascending gaits, we base on the proposed structure to generate such gaits and to establish a generalized GA fitness measure for evaluating the process of climbing stairs. The fitness measure falls into 6 stages, each of which specifies the absolute positions for each module of the snake robot as the evaluation standard. We conclude the standard and develop a generalized fitness measure. According to the sizes of each module, the total number of modules of the snake robot, the height of the stair, and the spatial relationships between them, we can infer all the absolute positions for each module of the snake robot in each stage. We further integrate Matlab Optimtool GA and Webots, a mobile robot simulation platform, along with the 6-stage fitness measure, to generate a series of angles for each module of the snake robot to accomplish the task of ascending stairs. Following that, we apply the series of angles, or the gait, to the snake robot in the real, physical world. One real-world result shows the gait for a 12-module snake robot with 16 cm stair is improved from an average deviation of 7 cm for each module between the final position of the snake robot and our aim to an average deviation of 4 cm for each module within the evolution of only 30 individuals for 30 generations, meaning that the integration of Matlab Optimtool GA and Webots along with our 6-stage fitness evaluation measure works for automatically generating the stair-climbing gait for snake robot to better move towards its aim position. Generally speaking, the resultant gait can be improved, making the snake robot reach closer to its aim position, by increasing the individuals or the generations in GA evolution, yet it may relatively take more time for GA to produce the resultant gait. Therefore, users can strike a balance between the final position of the snake robot and the time for GA evolution according to their needs. |
| Databáze: | Networked Digital Library of Theses & Dissertations |
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